PM566 Final Project
LA Galaxy U17 2022-2023 Season Game Data
Introduction
Catapult devices, equipped with GPS and inertial sensors like accelerometers, gyroscopes, and magnetometers, are wearable tracking technologies used in sports for performance monitoring. These devices provide detailed data by mapping athlete movements across three axes, making them a powerful tool for performance decisions. Used by the LA Galaxy Sports Performance Department, Catapult data has been integral in assessing performance readiness, rehabilitation, and training. As a USC Sports Science student and intern at LA Galaxy, I have been involved in collecting this data since January 2023 for the U17 2022-2023 season. While the data is usually visualized using Catapult’s Cloud or internal systems like Microsoft Azure, for this project, I’ve exported CSVs directly from Catapult for analysis. This study primarily focuses on evaluating how fatigue affects physical performance in soccer, specifically investigating variations in players’ maximum velocities between the first and second halves of games, and including an analysis of physical performance of the MLS Next Tournament where the team had to play five games in seven days.
Interactive Metric vs Player Load Plot
For some more initial visualization, I decided to look at the relationship between “Player Load”, which is defined by Catapult as “the sum of the accelerations across all axes of the internal tri-axial accelerometer during movement”, and a few other physical metrics. Specifically, I looked at scatterplot of Player Load vs Total Distance Covered, Total Number of Sprints, Explosive Efforts, and Total High Intensity Bouts. These interactive plots allow you to see which player each data point corresponds to and their exact values. As shown by these graphs, there is a strong positive correlation between Player Load and all examined physical metrics.
Maximum Velocity Analysis
A lot of my analysis was focused around looking at individual player’s high speeds. Here are some graphs showing highest velocities per player. The table shows how many times each player appeared in the Top 3 for highest speeds for each match.
| Player Name | Half | Times in Top 3 | Player Name | Half | Times in Top 3 |
|---|---|---|---|---|---|
| Player_14 | First Half | 22 | Player_14 | Second Half | 19 |
| Player_17 | First Half | 17 | Player_4 | Second Half | 14 |
| Player_3 | First Half | 14 | Player_12 | Second Half | 12 |
| Player_4 | First Half | 11 | Player_17 | Second Half | 12 |
| Player_7 | First Half | 11 | Player_7 | Second Half | 12 |
| Player_19 | First Half | 9 | Player_19 | Second Half | 11 |
| Player_12 | First Half | 8 | Player_21 | Second Half | 8 |
| Player_15 | First Half | 7 | Player_26 | Second Half | 7 |
| Player_10 | First Half | 6 | Player_3 | Second Half | 7 |
| Player_20 | First Half | 6 | Player_11 | Second Half | 6 |
Summary Table and Bar Charts for MLS Next Tournament Matches
The U17 Team Played 5 matches within 7 days in June 2023 in order to lift the MLS Next trophy. They played in hot and humid conditions in Texas. Here is a summary of their physical performance in these matches.
| Activity Name | Game Date | Total Distance | Total High Intensity Bouts | Total Player Load | Total Explosive Efforts | Total Sprints | Total High Speed Distance | Total Very High Speed Distance | Total Sprinting Distance | Total Supra Velocity Distance |
|---|---|---|---|---|---|---|---|---|---|---|
| U17 GD vs NYCFC | 2023-06-18 | 100962.69 | 468 | 9808.981 | 279 | 311 | 3741.93 | 691.55 | 244.39 | 35.18 |
| U17 GD vs Philadelphia | 2023-06-19 | 85746.10 | 438 | 8493.206 | 239 | 216 | 2843.61 | 651.58 | 216.41 | 60.81 |
| U17 GD vs TFA | 2023-06-21 | 91976.23 | 432 | 8732.986 | 255 | 269 | 3608.76 | 466.27 | 120.83 | 19.96 |
| U17 GD vs San Jose | 2023-06-23 | 108491.91 | 508 | 10766.929 | 283 | 304 | 3877.79 | 564.90 | 231.75 | 25.15 |
| U17 GD vs Real Colorado | 2023-06-25 | 99200.09 | 436 | 9329.604 | 236 | 230 | 2911.11 | 465.49 | 182.11 | 45.42 |
Interactive Sprint Distance and Physical Metrics Graphs
Here is an interactive graph showing the breakdown of distance covered at different speeds throughout the MLS Next Tournament, as well as match totals for physical metrics.